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SIGIR
2004
ACM

A search engine for historical manuscript images

9 years 3 months ago
A search engine for historical manuscript images
Many museum and library archives are digitizing their large collections of handwritten historical manuscripts to enable public access to them. These collections are only available in image formats and require expensive manual annotation work for access to them. Current handwriting recognizers have word error rates in excess of 50% and therefore cannot be used for such material. We describe two statistical models for retrieval in large collections of handwritten manuscripts given a text query. Both use a set of transcribed page images to learn a joint probability distribution between features computed from word images and their transcriptions. The models can then be used to retrieve unlabeled images of handwritten documents given a text query. We show experiments with a training set of 100 transcribed pages and a test set of 987 handwritten page images from the George Washington collection. Experiments show that the precision at 20 documents is about 0.4 to 0.5 depending on the model. ...
Toni M. Rath, R. Manmatha, Victor Lavrenko
Added 30 Jun 2010
Updated 30 Jun 2010
Type Conference
Year 2004
Where SIGIR
Authors Toni M. Rath, R. Manmatha, Victor Lavrenko
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